Good morning. Sapien has raised a new funding round led by Neo’s Ali Partovi at a $180 million valuation, as the two-year-old AI startup pushes beyond financial planning software into a broader system for analyzing how operational decisions affect a company’s bottom line. Its customers now include Bayer, Carlex, Cooper Standard, Blink Charging and Westgate Resorts.
The shift is reflected in how customers are using the platform. According to a forthcoming case study I was able to review on automotive supplier Carlex, Sapien rebuilt an existing profitability analysis and found that factors the company had identified as contributing $10 million in positive EBITDA were actually producing a $2 million drag.
Sapien later found another $1.5 million opportunity in a customer-channel pattern the team had not been looking for. The analysis took about 20 minutes.
“It took 20 minutes,” said Jason Waltz, business unit VP of finance for Carlex’s Aftermarket Division. “It would have probably taken us two weeks, and we probably wouldn’t have gotten to that level.”
That kind of analysis is increasingly the focus for Sapien, which founders Ron Nachum, Pranav Ravella, and Arya Grayeli launched in October 2024 with an $8.7 million seed round led by General Catalyst.
The company has also grown quickly, with headcount increasing fivefold over the past year, bringing together AI researchers and engineers from Meta, Google, and Palantir with executives and operators from McKinsey & Company, Blackstone, Barclays, and Plaid.
Nachum, Ravella, and Grayeli met in high school before attending Harvard, Stanford and the University of Texas at Austin, respectively.
From FP&A to operating decisions
When I first spoke with Nachum, who serves as CEO, two years ago, Sapien was focused on FP&A. The company has since moved toward a broader question: not just what happened to a company’s financial results, but what operational decisions caused them.
Nachum describes Sapien as a financial and operational system that connects the numbers in a company’s financial statements with the underlying business. The idea is to help finance and operating teams investigate changes in revenue, margins and cash flow, identify the drivers behind them and then act on those findings.
That is a different proposition from adding another dashboard or automating another report. Sapien is betting that AI can do more of the investigative work traditionally handled by finance and operating teams.
Carlex has since expanded its use of Sapien into pricing, inventory, customer orders, OEM quoting, supply chain and operations, Nachum said.
Cooper Standard and Blink Charging are using the platform in similar ways, according to the case studies, with analyses that previously took hours or days being reduced to minutes and teams using the results to identify potential savings and margin improvements.
The trust factor
For Nachum, the biggest obstacle to AI adoption in finance isn’t necessarily whether the technology can produce an answer.
“Every large company is data rich and analysis poor,” he said. The harder part, he argues, is getting finance teams to trust the answer—whether the underlying numbers are correct, the analysis is reliable and the company’s data remains secure.
That makes trust an important part of Sapien’s approach. Once teams become comfortable using the platform for financial analysis, Nachum said, its use can spread into functions such as supply chain, sales, and accounting.
The expansion also reflects Sapien’s broader shift away from being an FP&A tool. Rather than treating finance as a standalone function, the company is trying to connect financial outcomes to the operational decisions that produce them.
One of Nachum’s core bets has been to avoid turning the company into what he calls an “Excel copilot.” The goal, instead, is to build a system that can investigate a business, find important patterns and eventually help teams turn those findings into repeatable processes.
For Sapien, that is ultimately the bigger opportunity: using AI not simply to make existing financial work faster, but to find the operational decisions that can materially change a company’s financial performance.
Sheryl Estrada [email protected]
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